Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "18" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 30 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 30 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2460013 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 12.158105 | 7.878714 | 11.082803 | 0.069092 | 6.065287 | 3.839957 | 1.373820 | 58.235028 | 0.0351 | 0.3951 | 0.3191 | nan | nan |
| 2460012 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 11.383342 | 7.655806 | 10.899947 | 0.544992 | 6.471393 | 3.380622 | 1.418416 | 66.308719 | 0.0363 | 0.3708 | 0.2948 | nan | nan |
| 2460011 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 12.772999 | 8.707106 | 14.513651 | 0.577991 | 13.501062 | 6.213203 | 1.447148 | 57.829174 | 0.0363 | 0.3538 | 0.2799 | nan | nan |
| 2460010 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 13.716646 | 17.627679 | 11.660477 | 12.641219 | 9.237743 | 10.489350 | 1.263101 | 1.227752 | 0.0268 | 0.0249 | 0.0021 | nan | nan |
| 2460009 | RF_maintenance | 100.00% | 100.00% | 64.70% | 0.00% | - | - | 12.781795 | 19.380316 | 13.009673 | 0.175706 | 7.343555 | 3.777726 | 0.869591 | 15.357181 | 0.0294 | 0.2006 | 0.1489 | nan | nan |
| 2460008 | RF_maintenance | 100.00% | 100.00% | 34.65% | 0.00% | - | - | 15.425626 | 23.301894 | 14.233600 | 0.060157 | 6.660378 | 3.303770 | 4.430303 | 7.315141 | 0.0309 | 0.2308 | 0.1746 | nan | nan |
| 2460007 | RF_maintenance | 100.00% | 100.00% | 52.11% | 0.00% | - | - | 11.430409 | 16.811268 | 11.119392 | 0.231300 | 5.943673 | 3.244689 | 1.477660 | 15.052429 | 0.0298 | 0.2176 | 0.1632 | nan | nan |
| 2459999 | RF_maintenance | 0.00% | 100.00% | 98.91% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0282 | 0.0691 | 0.0376 | nan | nan |
| 2459998 | RF_maintenance | 100.00% | 100.00% | 51.22% | 0.00% | - | - | 9.732936 | 15.498495 | 9.510845 | -0.024692 | 8.020620 | 5.682713 | 0.681140 | 17.025595 | 0.0292 | 0.2125 | 0.1595 | nan | nan |
| 2459997 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459996 | RF_maintenance | 100.00% | 100.00% | 50.76% | 0.00% | - | - | 11.861972 | 19.312593 | 12.671403 | 0.385120 | 7.323177 | 4.205414 | 0.380722 | 14.181728 | 0.0291 | 0.2149 | 0.1628 | nan | nan |
| 2459995 | RF_maintenance | 100.00% | 100.00% | 41.46% | 0.00% | - | - | 12.085053 | 18.930840 | 11.752271 | -0.243652 | 8.084590 | 5.055614 | 0.342816 | 15.588865 | 0.0305 | 0.2255 | 0.1685 | nan | nan |
| 2459994 | RF_maintenance | 100.00% | 100.00% | 42.87% | 0.00% | - | - | 11.560768 | 18.103115 | 10.138308 | -0.086286 | 7.817983 | 5.300102 | 0.187329 | 14.611171 | 0.0293 | 0.2237 | 0.1677 | nan | nan |
| 2459993 | RF_maintenance | 100.00% | 100.00% | 81.28% | 0.00% | - | - | 12.761117 | 18.418596 | 9.418341 | -0.385753 | 10.242215 | 8.989051 | 0.705233 | 16.387015 | 0.0280 | 0.1883 | 0.1340 | nan | nan |
| 2459991 | RF_maintenance | 100.00% | 100.00% | 39.90% | 0.00% | - | - | 13.670223 | 20.563308 | 9.980625 | -0.415700 | 9.241352 | 5.930229 | 0.176857 | 16.657857 | 0.0298 | 0.2240 | 0.1695 | nan | nan |
| 2459990 | RF_maintenance | 100.00% | 100.00% | 42.87% | 0.00% | - | - | 11.044045 | 17.494147 | 9.769459 | -0.548520 | 9.130672 | 6.308599 | 0.020278 | 17.988628 | 0.0303 | 0.2260 | 0.1706 | nan | nan |
| 2459989 | RF_maintenance | 100.00% | 100.00% | 42.68% | 0.00% | - | - | 10.833011 | 18.008039 | 8.694610 | -0.206776 | 8.042283 | 4.780026 | -0.166424 | 11.850900 | 0.0288 | 0.2231 | 0.1684 | nan | nan |
| 2459988 | RF_maintenance | 100.00% | 100.00% | 47.19% | 0.00% | - | - | 12.978432 | 20.558207 | 10.081086 | -0.572499 | 10.821012 | 7.363604 | 0.006449 | 13.323511 | 0.0294 | 0.2208 | 0.1682 | nan | nan |
| 2459987 | RF_maintenance | 100.00% | 100.00% | 49.49% | 0.00% | - | - | 10.778859 | 17.586716 | 9.785501 | -0.111182 | 6.421602 | 4.607104 | 0.615140 | 20.631718 | 0.0295 | 0.2275 | 0.1728 | nan | nan |
| 2459986 | RF_maintenance | 100.00% | 100.00% | 35.37% | 0.00% | - | - | 13.427751 | 20.220950 | 10.714686 | -0.259506 | 9.446239 | 7.056657 | 5.399794 | 17.014200 | 0.0288 | 0.2449 | 0.1890 | nan | nan |
| 2459985 | RF_maintenance | 100.00% | 100.00% | 51.19% | 0.00% | - | - | 12.364061 | 19.847702 | 9.932025 | -0.133507 | 7.278299 | 4.474237 | 0.951656 | 23.720745 | 0.0297 | 0.2174 | 0.1663 | nan | nan |
| 2459984 | RF_maintenance | 100.00% | 100.00% | 53.70% | 0.00% | - | - | 11.810517 | 20.618816 | 10.309659 | 0.078739 | 9.415445 | 8.140085 | 2.023155 | 16.749410 | 0.0292 | 0.2287 | 0.1752 | nan | nan |
| 2459983 | RF_maintenance | 100.00% | 100.00% | 38.68% | 0.00% | - | - | 11.506145 | 19.025755 | 9.855880 | -0.420769 | 9.348449 | 7.781732 | 2.748548 | 18.437818 | 0.0308 | 0.2554 | 0.1981 | nan | nan |
| 2459982 | RF_maintenance | 100.00% | 100.00% | 12.59% | 0.00% | - | - | 9.910738 | 19.752902 | 8.371977 | -0.192266 | 4.543846 | 3.956493 | 2.354865 | 4.707320 | 0.0299 | 0.2894 | 0.2289 | nan | nan |
| 2459981 | RF_maintenance | 100.00% | 100.00% | 37.39% | 0.00% | - | - | 10.695776 | 17.232317 | 10.499792 | -0.818691 | 10.507719 | 7.774710 | 0.166602 | 20.538813 | 0.0309 | 0.2287 | 0.1744 | nan | nan |
| 2459980 | RF_maintenance | 100.00% | 100.00% | 34.79% | 0.00% | - | - | 10.537502 | 15.639358 | 9.440116 | -0.605384 | 9.089642 | 6.860529 | 5.051265 | 6.993976 | 0.0307 | 0.2693 | 0.2115 | nan | nan |
| 2459979 | RF_maintenance | 100.00% | 100.00% | 49.16% | 0.00% | - | - | 10.903191 | 17.573031 | 8.738774 | -0.699440 | 8.992758 | 5.798804 | -0.098845 | 15.713573 | 0.0312 | 0.2229 | 0.1733 | nan | nan |
| 2459978 | RF_maintenance | 100.00% | 100.00% | 48.97% | 0.00% | - | - | 11.022550 | 18.186774 | 9.492311 | -0.790311 | 9.397819 | 6.131507 | -0.111704 | 17.325256 | 0.0290 | 0.2232 | 0.1727 | nan | nan |
| 2459977 | RF_maintenance | 100.00% | 100.00% | 53.80% | 0.00% | - | - | 11.316922 | 16.893320 | 9.328582 | -0.427976 | 9.284730 | 7.176498 | -0.000341 | 17.528801 | 0.0302 | 0.2091 | 0.1591 | nan | nan |
| 2459976 | RF_maintenance | 100.00% | 100.00% | 47.46% | 0.00% | - | - | 11.253926 | 18.097681 | 9.813845 | -0.677999 | 9.486089 | 6.025958 | 0.596201 | 14.173615 | 0.0291 | 0.2253 | 0.1725 | nan | nan |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Temporal Discontinuties | 58.235028 | 12.158105 | 7.878714 | 11.082803 | 0.069092 | 6.065287 | 3.839957 | 1.373820 | 58.235028 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Temporal Discontinuties | 66.308719 | 11.383342 | 7.655806 | 10.899947 | 0.544992 | 6.471393 | 3.380622 | 1.418416 | 66.308719 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Temporal Discontinuties | 57.829174 | 12.772999 | 8.707106 | 14.513651 | 0.577991 | 13.501062 | 6.213203 | 1.447148 | 57.829174 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 17.627679 | 13.716646 | 17.627679 | 11.660477 | 12.641219 | 9.237743 | 10.489350 | 1.263101 | 1.227752 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 19.380316 | 12.781795 | 19.380316 | 13.009673 | 0.175706 | 7.343555 | 3.777726 | 0.869591 | 15.357181 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 23.301894 | 23.301894 | 15.425626 | 0.060157 | 14.233600 | 3.303770 | 6.660378 | 7.315141 | 4.430303 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 16.811268 | 11.430409 | 16.811268 | 11.119392 | 0.231300 | 5.943673 | 3.244689 | 1.477660 | 15.052429 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Temporal Discontinuties | 17.025595 | 9.732936 | 15.498495 | 9.510845 | -0.024692 | 8.020620 | 5.682713 | 0.681140 | 17.025595 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 19.312593 | 11.861972 | 19.312593 | 12.671403 | 0.385120 | 7.323177 | 4.205414 | 0.380722 | 14.181728 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 18.930840 | 12.085053 | 18.930840 | 11.752271 | -0.243652 | 8.084590 | 5.055614 | 0.342816 | 15.588865 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 18.103115 | 11.560768 | 18.103115 | 10.138308 | -0.086286 | 7.817983 | 5.300102 | 0.187329 | 14.611171 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 18.418596 | 12.761117 | 18.418596 | 9.418341 | -0.385753 | 10.242215 | 8.989051 | 0.705233 | 16.387015 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 20.563308 | 13.670223 | 20.563308 | 9.980625 | -0.415700 | 9.241352 | 5.930229 | 0.176857 | 16.657857 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Temporal Discontinuties | 17.988628 | 17.494147 | 11.044045 | -0.548520 | 9.769459 | 6.308599 | 9.130672 | 17.988628 | 0.020278 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 18.008039 | 18.008039 | 10.833011 | -0.206776 | 8.694610 | 4.780026 | 8.042283 | 11.850900 | -0.166424 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 20.558207 | 20.558207 | 12.978432 | -0.572499 | 10.081086 | 7.363604 | 10.821012 | 13.323511 | 0.006449 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Temporal Discontinuties | 20.631718 | 10.778859 | 17.586716 | 9.785501 | -0.111182 | 6.421602 | 4.607104 | 0.615140 | 20.631718 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 20.220950 | 20.220950 | 13.427751 | -0.259506 | 10.714686 | 7.056657 | 9.446239 | 17.014200 | 5.399794 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Temporal Discontinuties | 23.720745 | 19.847702 | 12.364061 | -0.133507 | 9.932025 | 4.474237 | 7.278299 | 23.720745 | 0.951656 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 20.618816 | 11.810517 | 20.618816 | 10.309659 | 0.078739 | 9.415445 | 8.140085 | 2.023155 | 16.749410 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 19.025755 | 11.506145 | 19.025755 | 9.855880 | -0.420769 | 9.348449 | 7.781732 | 2.748548 | 18.437818 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 19.752902 | 9.910738 | 19.752902 | 8.371977 | -0.192266 | 4.543846 | 3.956493 | 2.354865 | 4.707320 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Temporal Discontinuties | 20.538813 | 17.232317 | 10.695776 | -0.818691 | 10.499792 | 7.774710 | 10.507719 | 20.538813 | 0.166602 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 15.639358 | 15.639358 | 10.537502 | -0.605384 | 9.440116 | 6.860529 | 9.089642 | 6.993976 | 5.051265 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 17.573031 | 10.903191 | 17.573031 | 8.738774 | -0.699440 | 8.992758 | 5.798804 | -0.098845 | 15.713573 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 18.186774 | 18.186774 | 11.022550 | -0.790311 | 9.492311 | 6.131507 | 9.397819 | 17.325256 | -0.111704 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Temporal Discontinuties | 17.528801 | 11.316922 | 16.893320 | 9.328582 | -0.427976 | 9.284730 | 7.176498 | -0.000341 | 17.528801 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | N01 | RF_maintenance | nn Shape | 18.097681 | 18.097681 | 11.253926 | -0.677999 | 9.813845 | 6.025958 | 9.486089 | 14.173615 | 0.596201 |